Dear Bert Gunter,
Thank you for your advice. I will take care in the next post.
Best regards,
Nhat Tran.
Vào Th 3, 4 thg 12, 2018 vào lúc 23:16 Bert Gunter
đã viết:
> Please do not re-post. To increase your chance of getting a useful answer,
> read and follow the posting guide below, which
Your multiplication description sounds more like matrix multiplication than
scalar multiplication. R supports matrix multiplication with the %*% operator.
I didn't follow the rest of your description... are you doing a homework
assignment? There is a no homework policy on this list...
On Decemb
Hello I was wondering if anyone could help. I am using R to perform random
projection on Gaussians.
I need to take k Gaussian random vectors U1,...,Uk in R(reals)
Then for any vector v in d dimensions, perform the random projection:
f(v) = v.U1, v.U2, ..., v.Uk which reduces v from d dimensions
Hi,
I'm studying occurence of Behavior11, Behavior12,Behavior2,Behavior3 according
three variables :
Times : task time
Time_interval :task time in interval
Frequency:Frequency of the task
For this purpose, I use GLM
attach(datas)
an11=anova(glm(Behavior11 ~ Times + Frequency,
family=bino
Please do not re-post. To increase your chance of getting a useful answer,
read and follow the posting guide below, which you have not yet done. For
example, what is "F.cube", what packages are you using? Also, this list is
about R programming, not statistics, which is more what your query seems to
Hi,
It is because the print method for POSIXct likely tries to simplify. To see it
in the format you desire, you need to be explicit when calling it.
x = as.POSIXct('2018-11-2700:00:00', format = "%Y-%m-%d%H:%M:%S", tz = 'UTC')
format(x, "%Y-%m-%d %H:%M:%S %Z")
[1] "2018-11-27 00:00:00 UTC"
Ch
Hi,
I am trying to format my Character strings to POSIXct as below :
> as.POSIXct('2018-11-2700:00:00', format = "%Y-%m-%d%H:%M:%S", tz = 'UTC')
[1] "2018-11-27 UTC"
> as.POSIXct('2018-11-2701:00:00', format = "%Y-%m-%d%H:%M:%S", tz = 'UTC')
[1] "2018-11-27 01:00:00 UTC"
For the first case, I wa
Dear all,
I'm trying to use the D-optimum design. In my data, the response is KIC,
and 4 factors are AC, AV, T, and Temp. A typical second-degree response
modeling is as follows:
> data<-read.csv("2.csv", header =T)
> mod <-
lm(KIC~AC+I(AC^2)+AV+I(AV^2)+T+I(T^2)+Temp+I(Temp^2)+AC:AV+AC:T+AC:
Hello All,
The link below shows the 5 steps required to build a text cloud from a text
file of documents (e.g., posts, tweets, etc.).
http://www.sthda.com/english/wiki/text-mining-and-word-cloud-fundamentals-in-r-5-simple-steps-you-should-know
The R script in the link loads the text into a char
Dear list,
I'm trying to understand what kind of uncertainty intervals are
plotted for survival::survfit.coxph when 'conf.int=TRUE' is called,
e.g.:
f <- coxph(Surv(futime, fustat) ~ age, data = ovarian)
s <- survfit(f, newdata=data.frame(age=c(30, 60)))
plot(s, conf.int=TRUE)
Are these bands th
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